This invention relates to signal processing techniques; and more particularly, to the extraction of a sinusoidal waveform from a “noisy” signal.
In some troubleshooting applications; for example, in fault investigation of electric motors, it is often necessary to evaluate signals obtained as part of the troubleshooting process in order to determine the cause of a problem. In an electric motor, these problems may include broken rotor bars, or a turn-to-turn electrical short. During signal processing, the frequency of a signal of interest can be evaluated as a component of a major Fourier transformation. Further, while a particular frequency of interest might not be the major Fourier component, over all of a frequency range, the component may well be the highest amplitude signal component within a particular frequency band. Sometimes it is possible to initially select a frequency band sufficiently narrow so the frequency of interest is the major component within that narrow range of frequencies. On the other hand, many times the signal is so noisy that even if an evaluation can be attempted within a frequency band within close proximity to a signal of interest, the random noise present within the band may be significantly higher than the amplitude of the signal of interest. The result is that the signal of interest is obscured by the noise and cannot be readily identified or processed as part of troubleshooting the problem. Rather, the noise renders any meaningful search ineffective, at best yielding only a random result which is not helpful at all.
Further affecting the situation is the condition that the waveform of interest is often only of a short duration. This makes it difficult to capture the signal so it can be made available for analysis. Using conventional signal processing techniques for shorter waveforms, such as are known to those skilled in the art, a frequency of interest can sometimes be identified and recovered. One such method for detecting a specific frequency component within a signal spectrum requires that the signal be filtered to be within a desired frequency band that includes the frequency of interest. If the signal is then either the only significant component within the band, or a major component within the band, the signal can now be detected and processed.
The above described technique usually only works, however, if there is little or no noise in the filtered frequency band. More often, the peak amplitude of the signal of interest is too small when compared with the noise within the band and is buried too deeply within the noise to be extracted. In these situations, even if the researcher is within very close proximity to the signal that needs to be identified, the amplitude peaks in the frequency spectrum being investigated will be noise peaks rather than signal peaks and the signal of interest will remain hidden. The result is that other troubleshooting techniques have to be employed to identify the cause of the problem.